|ECR 2018 / C-1838|
|Multiparametric MRI in prostate cancer: a radiomic study on different diffusion and perfusion models|
Identified radiomic features differentiated PCa from benign PZ. Prediction performances were higher for diffusion features (extracted for both DWI and DKI - Fig1) than for perfusion ones (extracted for both the TM and the SSM - Fig2). These differences were confirmed independently by the number of features included in the logistic model (i.e., Model order). Intermodal approach lead to logistic regression models with very high discimination performances (AUC values close to 1) with best results for sensitivity, specificity and accuracy (more than 0.995) in the models including 4, 5, and 7 features (Fig3,4). These models were also able to significantly discriminate BPH from other groups (p<0.001 - Fig5).
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